Accession Number:

ADA151400

Title:

Two-Level Multifactor Designs for Detecting the Presence of Interactions,

Descriptive Note:

Corporate Author:

WISCONSIN UNIV-MADISON MATHEMATICS RESEARCH CENTER

Personal Author(s):

• Morris, M. D.
• Mitchell, T. J.

Report Date:

1983-11-01

Pagination or Media Count:

12.0

Abstract:

A design optimality criterion, trL-optimality, is applied to the problem of designing two-level multifactor experiments to detect the presence of interactions among the controlled variables. We give rules for constructing TRL-optimal foldover designs and trL-optimal fractional factorial designs. Some results are given on the power of these designs for testing the hypothesis that there are no two-factor interactions. Augmentation of the trL-optimal designs produces designs that achieve a compromise between the criteria of D- optimality for parameter estimation in a first-order model and trL- optimality for detecting the lack of fit. We give an example to demonstrate an application to the sensitivity analysis of a computer model. Originator-supplied keywords include Compromise design D-optimality Experimental design First order design Foldover design Fractional factorial design Main effects design Minimum aberration Optimal design Orthogonal array Resolution IV design Screening design Sensitivity analysis TrL-optimality.

Descriptors:

• *FACTORIAL DESIGN
• COMPUTERIZED SIMULATION
• DETECTION
• EXPERIMENTAL DESIGN
• HYPOTHESES
• INTERACTIONS
• OPTIMIZATION
• ORTHOGONALITY
• REPRINTS
• SENSITIVITY
• VARIABLES

Subject Categories:

• Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE